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## 	Replication Files: 
##	"Normalization of Censorship: Evidence from China"
##	Author: Tony Zirui Yang
##	Date: February 5, 2024
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## 	General Information:
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##
## 	1. Censorship Data
##	   
##	   Due to copy rights restrictions, privacy concerns, and research ethics 
##	   of sharing social media data from authoritarian regimes (as stipulated
##	   by the Institutional Review Board), the original censorship data is not
##	   included in the replication files. 
##
##	   The WeiboScope and WeChatScope data is acquired from their respective
##	   websites operated by Prof. King-wa Fu at the University of Hong Kong
##	   (email: kwfu@hku.hk). However, after the 2020 National Security Law
##	   in Hong Kong, the websites are no longer publicly accessible. Researchers 
##	   interested in accessing the data can directly contact Prof. Fu at HKU. 
##
##	   The FreeWeChat data is acquired from GreatFire.Org. Researchers 
##	   interested in accessing the data can directly contact Martin Johnson at 
##	   GreatFire.Org (email: martin@greatfire.org)
##
##	   In this replication file, only pre-processed censorship data and R codes
##	   operating the processed data are included. Please read Sections 4.1, 4.2,
##	   and D1 for more details about pre-processing.
##
##      2. Computational Requirements: 
##
##	   There are no specific computational requirements to run the code. 
##	   Any standard personal computer (multi-core) with R installed will 
##         be able to reproduce the results presented in the paper using the
##	   replication codes.
##	   
## 	3. R version and Operating System:
##	   
##	   R version: 4.3.2 (2023-10-31) -- "Eye Holes"
##         Operating System: macOS Ventura
##	   
## 	4. Required R-packages: 
##		
##	   Listed in each file
##
## 	5. Code: 
##	   
## 	   * Code that reproduces the main observational results (Figures, 
##	     Tables, and numbers reported) in the paper:
##
##		- "./01_Observational_Results_Paper.R"
##
## 	   * Code that reproduces the main experimental results (Figures, 
##	     Tables, and numbers reported) in the paper:
##
##		- "./02_Experimental_Results_Paper.R"
##
## 	   * Code that reproduces all observational results presented in the Appendix:
##
##		- "./03_Experimental_Results_Appendix.R"
##
## 	   * Code that reproduces all observational results presented in the Appendix:
##
##		- "./04_Observational_Results_Appendix.R"
##
## 	6. Data: 
##	   
## 	   * Data for the two survey experiments:
##
##		- "./Experiment.csv"
##
## 	   * Pre-processed censorship data from FreeWeChat:
##
##		- "./FreeWeChatResults.csv"
##
## 	   * Pre-processed censorship data from WeChatScope:
##
##		- "./WeChatScopeResults.csv"
##
## 	   * Pre-processed censorship data from WeiboScope:
##
##		- "./WeiboScopeResults.csv"
##
## 	   * Training data from the two human coders (Table D1):
##
##		- "./TableD1.csv"
##
## 	   * Pre-processed censorship data for testing model performance (Table E1):
##
##		- "./TableE1.csv"
##
## 	   * Pre-processed censorship data from five-fold cross-validation (Table E2):
##
##		- "./TableE2.csv"
##
## 	   * Pre-processed WeChatScope censorship data using Logistic Model (Table E3):
##
##		- "./TableE3.csv"
##
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## 	Codebook:
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##
## 	1. "./Experiment.csv"
##
##	Study: 1 - Study 1; 2 - Study 2.
##	Group: Blank - Blank Control Group; Control - Control Group;
##	       Treatment - Treatment Group.
##	Treatment: 0 - Control Group; 1 - Treatment Group.
##	Female: 0 - Male; 1 - Female.
##	Age_Group: 1 - <= 19 year-old; 2 - 20-24 year-old; 3 - 25-39 year-old;
##		   4 - 30-34 year-old; 5 - 35-39 year-old; 6 - 40-44 year-old; 
##		   7 - 45-49 year-old; 8 - >= 50 year-old.
##	Education: 1 - <= Junior High School; 2 - Senior High School; 3 - 3-year College; 
##		   4 - 4-year College; 5 - >= Postgraduate.
##	Income:    1 - <= 3000; 2 - 3000-5000; 3 - 5000-8000; 4 - 8000-10000; 3 - >=10000.
##	Party_Member: 0 - Not a CCP member; 1 - CCP member.
##	Ideology:  Five-point Likert Scale; 
##		   1 - strongly pro-state; 5 - strongly pro-market.
##	Political_Interest:  Six-point Scale; 1 - little interest; 5 - strong interest.
##	Social_Media:  Five-point Scale;
##		   1 - rarely use social media; 5 - use social media a lot.
##	Region:    1 - East; 2 - Central; 3 - West; 4 - Northeast.
##	Censor_Support:  Five-point Likert Scale;
##		   1 - strongly disagree with censorship;
##		   5 - strongly agree with censorship.
##	Censor_Content:   Seven-point Scale;
##		   1 - Censorship targets political content;
##		   7 - Censorship targets non-political content.
##	Censor_Political: Five-point Likert Scale;
##		   1 - strongly disagree with censorship of political content; 
##		   5 - strongly agree with censorship of political content. 
##	Censor_NonPolitical: Five-point Likert Scale;
##		   1 - strongly disagree with censorship of non-political content; 
##       	   5 - strongly agree with censorship of non-political content.
##	Regime_Overall:  Five-point Likert Scale;
##		   1 - strongly dissatisfied with China;
##		   5 - strongly satisfied with China.
##	Regime_Central:  Five-point Likert Scale;
##		   1 - strongly disagree that the central government works for the people;
##		   5 - strongly agree that the central government works for the people.
##	Regime_Local:  Five-point Likert Scale;
##		   1 - strongly disagree that the local government works for the people;
##		   5 - strongly agree that the local government works for the people.
##	Regime_Protest:  Five-point Likert Scale;
##		   1 - very unlikely to protest; 5 - very likely to protest.
##	Censor_Support_LE_T: 0 - Control list; 1 - Treated list.
##	Censor_Support_Implicit: 1 - Selected 0 item from the list; 
##				 2 - Selected 1 item from the list;
##				 3 - Selected 2 items from the list;
##				 4 - Selected 3 items from the list;
##				 5 - Selected 4 items from the list;
##	Occupation: 1 - Student; 2 - Self-employed; 3 - Corporate employee;
##		    4 - Corporate management; 5 - Government employee; 6 - Professional;##                  7 - Manufacturing; 8 - Service worker; 9 - Migrant worker; 
##		    10 - Farmer; 11 - Unemployed; 13 - Retired.
##	Urban: 1 - Rural area; 2 - Urban area.##
##
##
## 	2. "./FreeWeChatResults.csv" and "./WeChatScopeResults.csv" and "./WeiboScopeResults.csv"
## 	   "./TableD1.csv" and "./TableE1.csv" and "./TableE2.csv" and "./TableE3.csv"
##
##      Year: 	2016 - 2022
##	Month:	1 - 12
##	ADS: 	The number of censored articles in the advertisement category in that month.
##	BET: 	The number of censored articles in the business category in that month.
##	COL: 	The number of censored articles in the collective action category in that month.
##	CRI: 	The number of censored articles in the government criticism category in that month.
##	ESX: 	The number of censored articles in the entertainment category in that month.
##	FOR: 	The number of censored articles in the foreign category in that month.
##	GOV: 	The number of censored articles in the other government-related category in that month.
##	LCT: 	The number of censored articles in the cultral category in that month.
##	OTH: 	The number of censored articles in the residual category in that month.
##
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